Noncatalytic Endosialidase Enables Surface Capture of Small-Cell Lung Cancer Cells Utilizing Strong Dendrimer-Mediated Enzyme-Glycoprotein Interactions

Hao Jui Hsu, Helena Palka-Hamblin, Gaurang P. Bhide, Ja Hye Myung, Michael Cheong, Karen J. Colley, Seungpyo Hong

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Enumeration of circulating tumor cells (CTCs) of small-cell lung cancer (SCLC) patients has been shown to predict the disease progress and long-term survival. Most CTC detection methods rely on epithelial surface markers, such as epithelial cell adhesion molecule (EpCAM). However, this marker in SCLC is reported to be often downregulated after a variety of phenotypic changes, which impairs the reliability of EpCAM-based CTC detections. In this regard, the development of an alternative CTC detection method involving different CTC surface markers is in demand. In this study, we evaluated, for the first time to our knowledge, the feasibility of detecting SCLC CTCs using a noncatalytic endosialidase (EndoN Trap, EndoNt). This noncatalytic enzyme was chosen due to its high affinity to polysialic acid (polySia), a cell-surface glycan, that is highly expressed by SCLC tissue. Furthermore, this enzyme-based system was integrated into our dendrimer-mediated CTC capture platform to further enhance the capture efficiency via multivalent binding. We found that the EndoNt-immobilized surfaces could specifically capture polySia-positive SCLC cells and the binding between SCLC cells and EndoNt surfaces was further stabilized by dendrimer-mediated multivalent binding. When compared to the EpCAM-based capture, EndoNt significantly improved the capture efficiency of polySia-positive SCLC cells under flow due to its higher binding affinity (lower dissociation rate constants). These findings suggest that this enzyme-based CTC capture strategy has the potential to be used as a superior alternative to the commonly used EpCAM-based methods, particularly for those types of cancer that overexpress polySia.

Original languageEnglish
Pages (from-to)3670-3675
Number of pages6
JournalAnalytical Chemistry
Volume90
Issue number6
DOIs
Publication statusPublished - 2018 Mar 20

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry

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